Update app.py

app.py

@@ -1,2 +1,80 @@
+import streamlit as st
+import json
+import os
 from transformers import pipeline
-print(pipeline('sentiment-analysis')('Test'))
+
+STYLE_SAMPLES_FILE = "style_samples.json"
+
+def load_style_samples():
+    if os.path.exists(STYLE_SAMPLES_FILE):
+        with open(STYLE_SAMPLES_FILE, "r") as f:
+            return json.load(f)
+    return []
+
+@st.cache_resource(show_spinner=False)
+def load_pipeline():
+    # Replace model ID with a more powerful public LLM if you want
+    model_id = "google/flan-t5-base"  # For English text generation
+    gen_pipe = pipeline(
+        "text2text-generation",
+        model=model_id,
+        device_map="auto",
+        trust_remote_code=True
+    )
+    return gen_pipe
+
+pipe = load_pipeline()
+style_samples = load_style_samples()
+
+st.set_page_config(page_title="LinkedIn Post Generator", layout="centered")
+st.title("🔗 LinkedIn Post Generator (Hugging Face)")
+st.write("Generate LinkedIn posts in your writing style.")
+
+with st.form("gen_form"):
+    topic = st.text_input("Post Topic", "Generative AI for Business")
+    tone = st.selectbox("Tone", ["Professional", "Friendly", "Inspirational", "Technical", "Concise"])
+    audience = st.text_input("Audience", "Startup founders")
+    length = st.slider("Length (approx words)", 30, 400, 120, 10)
+    use_sample = st.selectbox(
+        "Style Sample (optional)", ["None"] + [f"Sample {i+1}" for i in range(len(style_samples))])
+    custom_style = st.text_area("Or paste your own style sample (optional)")
+    submitted = st.form_submit_button("Generate Post")
+
+prompt_style = ""
+if use_sample != "None":
+    sample_idx = int(use_sample.split()[1]) - 1
+    prompt_style += f"Sample style: {style_samples[sample_idx]}\n"
+if custom_style.strip():
+    prompt_style += f"User style: {custom_style}\n"
+
+prompt = (
+    f"Write a LinkedIn post on '{topic}'.\n"
+    f"Tone: {tone}. Audience: {audience}. Length: about {length} words.\n"
+    f"{prompt_style}"
+    "Write in engaging, natural language, and end with a strong call to action."
+)
+
+if submitted:
+    if not topic.strip():
+        st.warning("Please enter a topic before generating.")
+    else:
+        with st.spinner("Generating..."):
+            try:
+                result = pipe(prompt, max_new_tokens=length + 32)[0]["generated_text"].strip()
+                st.success("Here's your LinkedIn post:")
+                st.write(result)
+                st.download_button("Download post as .txt", result, file_name="linkedin_post.txt")
+            except Exception as e:
+                st.error(f"Error generating post: {e}")
+
+st.markdown("---")
+st.write("Upload a new list of style samples (JSON array of strings, replaces existing):")
+file = st.file_uploader("Upload style_samples.json", type=["json"])
+if file:
+    try:
+        data = json.load(file)
+        with open(STYLE_SAMPLES_FILE, "w") as f:
+            json.dump(data, f)
+        st.success(f"Uploaded and saved {len(data)} samples. Reload Space to use.")
+    except Exception as e:
+        st.error(f"Upload failed: {e}")